Classification of multichannel EEG signal by single layer perceptron learning algorithm
Motor imagery (MI) related Electroencephalogram (EEG) signal classification is one of the main challenge in designing a brain computer interface (BCI) system. Single Layer Perceptron Learning (SLPL) algorithm has a very low computational requirement which makes it suitable for online BCI system...
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2014
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my.iium.irep.390012017-09-20T10:41:19Z http://irep.iium.edu.my/39001/ Classification of multichannel EEG signal by single layer perceptron learning algorithm Hasan, Mohammad Rubaiyat Ibrahimy, Muhammad Ibn Motakabber, S. M. A. Shahid, Shahjahan T Technology (General) Motor imagery (MI) related Electroencephalogram (EEG) signal classification is one of the main challenge in designing a brain computer interface (BCI) system. Single Layer Perceptron Learning (SLPL) algorithm has a very low computational requirement which makes it suitable for online BCI system. This paper proposes an advanced and simple classification technique for MI related BCI system. Initially the signal is extracted for different features. The SLPL classifier has been used to propose technique to design an MI based BCI. For contrastive comparison with other classification techniques have been evaluated by classification accuracy, mutual information and Cohen’s kappa. 2014-09 Conference or Workshop Item REM application/pdf en http://irep.iium.edu.my/39001/1/39001_edited.pdf application/pdf en http://irep.iium.edu.my/39001/4/39001_Classification%20of%20multichannel%20EEG%20signal_Scopus.pdf Hasan, Mohammad Rubaiyat and Ibrahimy, Muhammad Ibn and Motakabber, S. M. A. and Shahid, Shahjahan (2014) Classification of multichannel EEG signal by single layer perceptron learning algorithm. In: 5th International Conference on Computer and Communication Engineering (ICCCE 2014), 23th - 25th September 2014, Sunway Putra Hotel, Kuala Lumpur. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7031650 |
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T Technology (General) Hasan, Mohammad Rubaiyat Ibrahimy, Muhammad Ibn Motakabber, S. M. A. Shahid, Shahjahan Classification of multichannel EEG signal by single layer perceptron learning algorithm |
description |
Motor imagery (MI) related Electroencephalogram
(EEG) signal classification is one of the main challenge in
designing a brain computer interface (BCI) system. Single Layer
Perceptron Learning (SLPL) algorithm has a very low
computational requirement which makes it suitable for online
BCI system. This paper proposes an advanced and simple
classification technique for MI related BCI system. Initially the
signal is extracted for different features. The SLPL classifier has
been used to propose technique to design an MI based BCI. For
contrastive comparison with other classification techniques have
been evaluated by classification accuracy, mutual information
and Cohen’s kappa. |
format |
Conference or Workshop Item |
author |
Hasan, Mohammad Rubaiyat Ibrahimy, Muhammad Ibn Motakabber, S. M. A. Shahid, Shahjahan |
author_facet |
Hasan, Mohammad Rubaiyat Ibrahimy, Muhammad Ibn Motakabber, S. M. A. Shahid, Shahjahan |
author_sort |
Hasan, Mohammad Rubaiyat |
title |
Classification of multichannel EEG signal by single layer perceptron learning algorithm |
title_short |
Classification of multichannel EEG signal by single layer perceptron learning algorithm |
title_full |
Classification of multichannel EEG signal by single layer perceptron learning algorithm |
title_fullStr |
Classification of multichannel EEG signal by single layer perceptron learning algorithm |
title_full_unstemmed |
Classification of multichannel EEG signal by single layer perceptron learning algorithm |
title_sort |
classification of multichannel eeg signal by single layer perceptron learning algorithm |
publishDate |
2014 |
url |
http://irep.iium.edu.my/39001/1/39001_edited.pdf http://irep.iium.edu.my/39001/4/39001_Classification%20of%20multichannel%20EEG%20signal_Scopus.pdf http://irep.iium.edu.my/39001/ http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7031650 |
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1643611541691432960 |
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13.211869 |